A Markov random field model for network-based analysis of genomic data

Bioinformatics

Volumn 23, Issue 12, 2007, Pages 1537-1544

  Wei, Zhi ^a   Li, Hongzhe ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BREAST CANCER; CANCER RECURRENCE; CANCER SURVIVAL; DNA MICROARRAY; GENE EXPRESSION; GENE IDENTIFICATION; GENETIC ANALYSIS; GENETIC DATABASE; HUMAN; PHENOTYPE; PRIORITY JOURNAL; PROBABILITY; SENSITIVITY ANALYSIS; SIMULATION; STATISTICAL MODEL; UNIVARIATE ANALYSIS;

EID: 34547844074     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btm129     Document Type: Article

References (34)

1. Barker,N. and Clevers,H. (2006) Mining the Wnt pathway for cancer therapeutics. Nat. Rev. Drug Discov., 5, 997-1014.
2. Benjamini,Y. and Horchberg,Y. (1995) Controling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B, 57, 289-300.
3. Besag,J. (1986) On the statistical analysis of dirty pictures. J. R. Stat. Soc. B, 48, 259-302.
4. Burke,D. et al. (1998) Fibroblast growth factor receptors: Lessons from the genes. Trends Biochem. Sci., 23, 59-62.
5. Deng,M.H. et al. (2004) Integrated probabilistic model for functional prediction of proteins. J. Comput. Biol., 11, 463-476.
6. Deng,M.H. et al. (2002) Prediction of protein function using protein-protein interaction data. In The First IEEE Computer Society Bioinformatics Conference, CSB2002, pp. 117-126.
7. Dudoit,S. et al. (2002) Statistucal methods for identifying differentially expressed genes in replicated cDNA microarray experiments. Stat. Sin., 12, 111-139.
8. Efron,B. et al. (2001) Empirical Bayes Analysis of Microarray Experiment J. Am. Stat. Assoc., 96, 1151-1160.
9. Hewitt,K.J. et al. (2006) The claudin gene family: Expression in normal and neoplastic tissues. BMC Cancer, 6, 186.
10. Igarashi,T. et al. (2004) Divergent cyclin B1 expression and Rb/ p16/cyclin D1 pathway aberrations among pulmonary neuroendocrine tumors. Mod. Pathol., 17, 1259-1267.
11. Kanehisa,M. and Goto,S. (2002) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res., 28, 27-30.
12. Kendziorski,C.M. et al. (2003) On paramertic empirical Bayes methods for comparing multiple groups using replicated gene expressionm profiles. Stat. Med., 22, 3899-3914.
13. Lahad,J.P. et al. (2005) Stem cell ness: A "magic marker" for cancer. J. Clin. Invest., 115, 1463-1467.
14. Letovsky,S. and Kasif,S. (2003) Predicting protein function from protein/ protein interaction data: A probabilistic approach. Bioinformatics 19 (Suppl. 1) i197-i204.
15. Lönnstedt I. and Speed,T. (2002) Replicated microarray data. Stat. Sin., 12, 31-46.
16. Miller,L.D. et al. (2005) An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. Proc. Natl Acad. Sci., 102, 13550-13555.
17. Morin,P.J. (2005) Claudin proteins in human cancer: Promising new targets for diagnosis and therapy. Cancer Res., 65, 9603-9606.
18. Muller,A. et al. (2001) Involvement of chemokine receptors in breast cancer metastasis. Nature, 410, 50-56.
19. Nacu,S. et al. (2006) Gene expression network analysis, and applications to immunity. Technical report. Department of Statistics, Stanford Univerisity.
20. Newton,M.A. et al. (2001) On differntial variability of expression ratios: Improving statistical inference abou gene expression changes from micorarray data. J. Comput. Biol., 8, 37-52.
21. Rahnenführer, J. et al. (2004) Calculating the statistical significance of changes in pathway activity from gene expression data. Stat. Appl. Genet. Mol. Biol., 3, Article 16.
22. Rapaport,F. et al. (2007) Classification of microarray data using gene networks. BMC Bioinformatics. Feb 1;8, 35.
23. Rubie,C. et al. (2006) Chemokine receptor CCR6 expression in colorectal liver metastasis. J. Clin. Oncol., 24, 5173-5174.
24. Sagara,Y. et al. (2004) Clinical significance of Caveolin-1, Caveolin-2 and HER2/neu mRNA expression in human breast cancer. Br. J. Cancer, 91, 959-965.
25. Segal,E. et al. (2003) Discovering Molecular Pathways from Protein Interaction and Gene Expression Data. Bioinformatics, 19 (Suppl. 1), 264-272.
26. Shulewitz,M. et al. (2006) Repressor roles for TCF-4 and Sfrp1 in Wnt signaling in breast cancer. Oncogene, 25, 4361-9.
27. Sivachenko,A. et al. (2005) Identifying Local Gene Expression Patterns in Biomolecular Networks. In Proceedings of 2005 IEEE Computational Systems Bioinformatics Conference, Stanford, California.
28. Souaze,F. et al. (2006) Expression of neurotensin and NT1 receptor in human breast cancer: A potential role in tumor progression. Cancer Res., 66, 6243-9.
29. Subramanian,A. et al. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA., 102, 15545-50.
30. Tian,L. et al. (2005) Discovering statistically significant pathways in expression profiling studies. Proc. Natl Acad. Sci., 103, 13544-13549.
31. Tusher,V. et al. (2001) Significance analyusis of miocrarrays applied to ionizing radiation response. Proc. Natl Acad. Sci., 98, 5116-5121.
32. Wang,Y. et al. (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet, 365, 671-9.
33. Yu,K. et al. (2006) A modular analysis of breast cancer reveals a novel low-grade molecular signature in estrogen receptor positive tumors. Clin. Cancer Res., 12, 3288-3296.
34. Zhao,M. et al. (2006) Expression profiling of cyclin B1 and D1 in cervical carcinoma. Exp. Oncol., 28, 44-48.